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David Botstein,
director of Princeton’s Lewis-Sigler Institute for Integrative
Genomics, in a conference room designed inside a sculpture by architect
Frank Gehry. (Jon Roemer)

David
Botstein’s new biology The head of Princeton’s young genomics institute
is pioneering a science curriculum that is gaining national attention

By Kenneth H. Chang ’87

Shirley Tilghman admits that she was taken slightly aback when she answered
the phone nine months after becoming Princeton’s president four
years ago. On the line was David Botstein, head of a top research lab
at Stanford University and a pioneer of the Human Genome Project.

“He said, ‘I hear your job is open,’” Tilghman
recalls. She thought rumors were swirling that her presidential reign
was in trouble.

“No, no, no, your old job,” said Botstein, referring to
her vacated position as director of Princeton’s Lewis-Sigler Institute
for Integrative Genomics, which studies how genes function together. He
wanted to apply.

Tilghman asked why a man who led a laboratory of 30 scientists working
on cutting-edge cancer research would want to come to a relatively new
venture — it was then only three years old — and was impressed
by his response: “Because I think we have to teach biology completely
differently in the 21st century, and Princeton is the only place that
is going to take me seriously.”

He got the job.

Biology was once a science mostly of observation and description, relying
on persistence in arduous experiments that produced a morsel of knowledge.
Genetics researchers labored for years to pin the location of a single
gene. But today, with the genetic code fully unraveled for numerous creatures,
from viruses to yeast to mice to people, biologists have, in essence,
the lists of parts that make up the organisms, and they’re looking
to deduce the operating manuals. Sequencing of entire genomes is performed
en masse by machines, and the challenge is how to analyze the avalanche
of data that pours out. Tracking the on-and-off switching of thousands
of genes is as daunting as tracking inventory across thousands of Wal-Marts.

The Rafael Viñoly-designed
Carl Icahn Laboratory, home of the genomics institute, contains
31 vertical louvers that increase energy efficiency and, through
their shadows in the atrium, recall the double helix in DNA. (Ramon
Vinoly)

The Icahn Lab
atrium, with a conference area designed by Frank Gehry, at left,
was meant to encourage conversation and collaborations among scholars
in different disciplines.

Viñoly’s
building design includes lab spaces that can be taken apart and
rearranged to adapt to new developments and to promote collaborations
among researchers.

(Photographs
by Ramon Vinoly)

And so Botstein’s small institute has a grand ambition: understanding
how all the pieces of biology that have been discovered in recent decades
fit together into a functioning machine.

“Biology is fundamentally changed in the last five years,”
Tilghman says. “There’s now an opportunity to ask entirely
new questions that could not be asked before.” These new questions
include those being asked, for example, by Professor John Hopfield, a
physicist-turned-molecular-biologist who is using a computer science approach
to explore how neurons code and compute information; and by physics professor
William Bialek, who is working to understand the complex patterns in nerve
signals.

The “new” biology requires top quantitative skills as well
as an understanding of other sciences. At Princeton, one result is a new,
yearlong curriculum that is, Botstein says, “unlike anything taught
anywhere to undergraduates.” He believes that a mix of chemistry,
physics, computer science, and even mathematics needs to be added to biology
education — so much that the new Princeton curriculum will provide
a good foundation for students majoring in those fields as well, he says.
The new, full-year course has an unwieldy identifier — CHM/COS/
MOL/PHY 231-4 — that reflects the contributing departments: chemistry,
computer science, molecular biology, and physics. The name of the course
also does not roll off the tongue: An Integrated, Quantitative Introduction
to the Natural Sciences.

The weekly time commitment is large enough — five hours of lectures,
a three-hour laboratory, a three-hour computational laboratory, and an
optional evening problem session — that it counts for double credits.
Teaching the classes are two molecular biologists, two chemists, two physicists,
and two computer scientists. “It’s like Noah’s ark,”
Botstein says.

At 62, his bushy hair turning gray, Botstein has been one of the pioneers
in genetics, and he wants to train the next generation. “I’m
not going to be in this business for that much longer,” he says,
“and this seemed like a great last big effort.”

The scope of the curriculum reflects Botstein’s own eclectic education,
which, he admits, “had almost no biology in it.” An immigrant
from Switzerland — his family moved to New York after World War
II when he was 7 — Botstein graduated from the high-powered Bronx
High School of Science, then, in 1959, headed to Harvard. He briefly considered
a musical path, like that followed by brother Leon, now president of Bard
College and music director of the American Symphony Orchestra, but he
decided on science, planning to study physics.

Physics, however, was too crowded. Botstein found others to be better
at the mathematics — “I wasn’t really competitive as
a theoretiker,” he says — so he shifted more to the experimental
side, helping to build instruments for high-energy physics experiments.
“I was headed for being a modest-sized cog in a very large machine
involving hundreds of physicists,” he says. Biology, on the other
hand, was still something that a single scientist could explore. “I
could do an experiment in the morning and interpret it the next day or
even that evening,” he says. “The comparison didn’t
stand up. In biology I could do everything myself, and it was all fun.”

His undergraduate course load consisted of heapings of physical chemistry
and physics and only a single biology lab class. But biology already had
begun to change and Botstein found himself, in time and place, ahead of
the curve.

In 1956, James Watson arrived at Harvard as a professor, three years
after he and Francis Crick deduced that a spiraling staircase of a molecule
– deoxyribonucleic acid, or DNA – provided the blueprint for
every living organism. Though the alphabet used in DNA consists of only
four “letters,” variations in the sequence of letters produce
thousands of proteins.

Watson, Botstein recalls, “was making the argument that biology
was going to change, that it was going to become molecular, and that the
issues of interest were the issues of information transfer from the DNA,
which was obviously the information carrier, to the proteins, which were
obviously doing the work in the cell. That was obvious to him, then. It
wasn’t so obvious to everyone else. But he converted a bunch of
young people to his point of view, and I was among them. In fact, it was
physicists who were among the first converts.”

Botstein received a bachelor’s degree in biochemical sciences
at Harvard and then a Ph.D. in genetics at the University of Michigan.
He taught for 20 years at MIT, working primarily on the genetics of yeast.
Then he moved to private industry and became vice president at Genentech
for two years, before returning to academia at Stanford.

Along the way, he pulled a host of people into the field, including
Eric S. Lander ’78. Lander, now director of the Broad Institute
for Genomic Research in Cambridge, Mass., recalls a colleague introducing
him to Botstein in 1985 as “this mathematician learning genetics.”

At the time, Lander, who majored in math, was on leave from a professorship
at Harvard Business School to follow an interest in biology. A “mathematician
learning genetics” turned out to be exactly what Botstein was looking
for. “David immediately launched into some wonderfully bombastic
Botsteinian discourse about what the challenges would be,” Lander
recalls.

Lander started working with Botstein the next day, and within a couple
of months they had worked out the mathematics needed to keep track of
so many genes, so that they would not be awash in data. “It was
David who sucked me into what became the Human Genome Project,”
the massive project to read the entire sequence of 3 billion letters in
a strand of human DNA and identify the 20,000 to 25,000 genes embedded
in it, Lander says.

Botstein also came up with a crucial insight that provided the underpinnings
of the genome project. Lander explains that, at a conference in 1978 —
he was not present but has heard the story many times — genetics
researchers were discussing a particular genetic disease and how they
might be able to determine whether it was a dominant gene or a recessive
one, and how hard it was to zoom in on it. Botstein blurted out, “Well,
all you really need is a nearby genetic marker.”

Botstein, working on yeast, had figured out how to find markers, almost
like signposts, in the yeast genome. From these, geneticists could construct
a general map of the genome that would help them locate genes.

When others were still thinking one gene at a time, Botstein already
had foreseen how an advance in yeast genetics could be applied to people,
producing a genome-wide map that could be used for disease research. “That
insight comes to him in a moment,” says Daphne Preuss, a former
graduate student of Botstein’s who is now a professor at the University
of Chicago. “It shows going from here to there in a big jump.”

Two years ago, Botstein was at Stanford, where his renowned lab helped
to develop “gene chips” — slides on which pieces of
DNA are affixed – that can be used to identify different subtypes
of cancer, and that could lead to better diagnoses and help doctors tailor
more effective treatments. He had hooked up with Patrick Brown, a Stanford
biochemistry professor who had originated a simple way to make the chips,
known more technically as microarrays. With the sequencing of full genomes,
scientists can now place a sample of each of thousands of genes of an
organism (a gene is just a section of DNA that provides the blueprint
to build a protein) on a glass slide. They then can compare the behavior
of genes in a normal cell (which they tag with a green dye) with those
that have been stressed with heat or that have become cancerous (tagged
red). The cells are broken up and their genetic material is placed on
the slide. Some of the locations light up, indicating which genes are
active in the cells. The green and red hues tell whether the functions
are normal or unusual. By seeing which genes switch on and off in unison,
scientists also can identify new genes that are involved in a process.

For example, using these gene chips, Botstein and Brown have identified
four types of breast cancer that differ in their genetic makeup, something
that never would have been learned from just looking at the tumors.

That makes a crucial difference for a drug like Herceptin, developed
by Genentech. When evaluated against all four types, the data make the
drug look useless, but it has been shown to extend the lives of women
with one breast cancer type. In the overall test data, the benefit was
washed out by the ineffectiveness among the larger group and it became
apparent only when researchers could focus in on the smaller group.

Botstein says he does not miss this research, left behind in California.
He says he does miss the weather.

To understand the challenge of getting students up to speed in this
accelerating revolution in biology, consider a lab session last fall in
the basement of Princeton’s Carl Icahn Laboratory. The experiment
used nothing that was alive or ever had been alive — save for the
students and instructors.

One day, 20 freshmen dropped tiny aluminum ball bearings into cylinders
filled with glycerin, a clear liquid as thick as honey. They captured
the slow fall of the bearings with a video camera and plotted the motion
on a computer, all to measure the force of gravity. A few weeks later,
they would build simple electronic light sensors, and learn the Java computer
programming language. At times it seemed like a physics or engineering
class, but it may be the future of biology education.

The ball-bearings-in-glycerin experiment teaches the same thing as rolling
balls down inclined planes, a standard experiment conducted in freshman
physics classes to demonstrate the acceleration of gravity. In this lab,
however, the instructors also wanted to give students the experience of
measuring forces of something moving within a liquid. The action of life
happens within cells that, after all, are bags of water.

“We’re trying to build some intuition about physics concepts
that aren’t so intuitive,” says institute researcher William
Ryu ’94, one of the designers of the lab. At the same time, he says,
they try to “add a biological flavor.”

To measure the speed of the falling ball bearings, the students first
used rulers and stopwatches, just as in a typical physics class. But then
they switched to the video cameras and used the computers to plot and
calculate the velocity. In a later class, the students would measure the
growth of bacteria colonies. But instead of looking through a microscope
to count the colonies one by one, students shined a light through the
dish and measured how much light was blocked: the more bacteria, the less
light passing through. Ryu designed the simple light meter that the students
built as part of the experiment. “Ancient principles with modern
equipment,” says Botstein, summing up the underlying philosophy.

To some, the high-tech equipment is a shortcut that diminishes the students’
understanding of the underlying biology; in a way, the debate is a high-end
version of the argument over whether calculators should be allowed in
math classes in elementary schools. Botstein forcefully comes down on
the side of the computers and calls the withholding of such tools from
students “hazing.”

“We think we can teach a lot more that’s useful ... if we
don’t have to calculate everything in our heads,” he says.
“If you want to ask whether Euler or Newton or Gauss would have
liked the computer, there is no question. They wasted endless amounts
of time calculating things. ...Why are we teaching our students to do
without those things? Do we think there’s going to be a future with
no electricity, no computers?”

In Princeton’s curriculum, students are given a unified picture,
instead of different aspects of the same topic. In discussing atoms, for
example, a professor in a typical chemistry class might focus on how the
electron orbits interact as different atoms bond together, while a physics
professor might only discuss hydrogen, the simplest atom, and explain
all its quantum nuances. But rarely would students learn how the two approaches
come together. Similarly, in teaching statistics, most classes begin with
the flipping of coins. In the new course, the instructors, teaching the
same concepts, used a biological example: genes. “It makes it vivid,
concrete,” says Lubert Stryer of Stanford University, who chaired
a National Academies of Science committee that a couple of years ago criticized
the typical college biology curriculum as inadequate, and who visited
the new Princeton class recently. “There you can see the role of
chance in generating diversity. That was wonderful. They start probability
with [father of genetics Gregor] Mendel and not with flipping coins.”

Stryer says the new curriculum shows students how to move from the tremendous
volume of raw data to the “biological insight,” explaining,
“We need to educate men and women who ... have an intuitive feeling
for quantitative thinking.” After his visit to Princeton, he described
the new curriculum as “something really novel and very much in line”
with what the NAS committee had hoped for.

Botstein hopes that the new curriculum — and the institute itself
— will produce physicists and chemists who can talk to biologists,
and vice versa. Both the physical design of the Icahn Lab, which houses
the institute, and its scholarly agenda were designed to promote the collaborations
Botstein envisioned, with faculty members drawn from across Princeton’s
science and engineering departments. Architect Rafael Viñoly planned
the lab to have large blocks of lab and office space that can support
any kind of work, and offices for scholars doing computational research
are sprinkled among those for researchers working on bench-top experiments.

Last year, the National Institute of General Medical Sciences, part
of the National Institutes of Health, established a new center at Princeton
— with Botstein as its director — to use advanced computational
methods to explore how biological molecules interact with each other and
their environment to create new systems. The new center, which came with
an immediate grant of $3 million and a total pledge of almost $15 million
over five years, relies heavily on Botstein’s integrated, multidisciplinary
approach.

How to measure success? Botstein says there is no easy measure. He hopes
a large fraction of the 38 students in the new course will go on to graduate
school. (At present, more than two-thirds of Princeton’s physics
majors and 10 to 15 percent of its molecular biology majors continue in
academic science, though other students attend medical school.)

“If we increase the number of students who are motivated to become
professional scientists, we will regard that as a big success,”
he says. “We will have added nontrivially to the number of American
scientists. Whereas science is becoming a larger and larger fraction of
our culture and economy, a smaller and smaller fraction of those who are
arguably the best students in the world are going into it.”